<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>ASU | Mohamed Ghalwash</title><link>https://m-fakhry.github.io/tags/asu/</link><atom:link href="https://m-fakhry.github.io/tags/asu/index.xml" rel="self" type="application/rss+xml"/><description>ASU</description><generator>HugoBlox Kit (https://hugoblox.com)</generator><language>en-us</language><lastBuildDate>Thu, 01 Oct 2026 00:00:00 +0000</lastBuildDate><image><url>https://m-fakhry.github.io/media/icon_hu_1c0e9cb08cfb822a.png</url><title>ASU</title><link>https://m-fakhry.github.io/tags/asu/</link></image><item><title>Integration of Artificial Intelligence and Immunoinformatics Approach for Developing Novel Vaccine Strategies for Foot and Mouth Disease</title><link>https://m-fakhry.github.io/projects/fmd-epitope-vaccine/</link><pubDate>Thu, 01 Oct 2026 00:00:00 +0000</pubDate><guid>https://m-fakhry.github.io/projects/fmd-epitope-vaccine/</guid><description>&lt;p&gt;Foot and Mouth Disease (FMD) threatens global livestock and food security, yet existing vaccines struggle with the virus&amp;rsquo;s high genetic variability and limited cross-protection across serotypes. This project uses AI to design a universal chimeric vaccine — a multiepitope recombinant protein spanning the VP1, VP2, and VP3 viral proteins — capable of triggering cross-protective immunity across FMDV serotypes, alongside a model for predicting outbreak risk from case and virus-detection data.&lt;/p&gt;</description></item></channel></rss>